Abstract
Apart from the effects of treating those infected with COVID-19, the pandemic has also affected treatment for other diseases, which has been either interrupted or canceled. The aim of this paper is to provide a financial model for obtaining the cost overrun resulting from the worsening of illnesses and deaths for each of the causes considered. To achieve this, first deaths have been classified into causes of death and for each of these causes, an estimation has been made of the worsening condition of patients due to delay in treatment. Through these data, a fuzzy relation between deaths and the worsening condition of patients can be obtained. Next, the expertise process has been used to estimate cost overrun in relation to patients’ pathologies. The experts’ opinions have been aggregated using ordered weighted average (OWA). Lastly, using fuzzy logic again, a correction coefficient has been determined, which optimizes the future implementation of the proposed model without the need for a new estimation of inputs. The paper concludes with a numerical example for a better comprehension of the proposed theoretical model. Ultimately, it provides the scientific community in general and in particular managers of public administration entities with a novel tool for improving the efficiency of the healthcare system.
Highlights
On 31st January 2020, the first COVID-19 case was reported in Spain, followed by an exponential increase in the number of people infected
Through the mathematical model developed in this paper, it is possible to obtain the healthcare cost resulting from the worsening of pathologies because of delays in treatment
In order to do this, an analysis and classification over time are made of deaths caused by a certain pathology and patients whose pathology has become worse due to a delay in treatment
Summary
On 31st January 2020, the first COVID-19 case was reported in Spain, followed by an exponential increase in the number of people infected. A great number of surgeries have been cancelled or delayed due to the pandemic [1], and Klocker et al [2] highlight serious problems and even psychological effects experienced by patients. Atreya et al [3] affirm a 44% decrease in hospital admissions of patients without COVID-19. On many occasions it has been the citizens themselves who have decided of their own freewill not to use the health services because they are afraid of becoming infected or of saturating the system [4]
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